The grid should be as fine as computational costs allow; [1]} recommend that successive decreasing values of \(\lambda _1\)  differ by no more than a factor of 0.9, and for \(\lambda _2\)  we chose four grid points in simulations and seven for the data application. Final choice of \((\lambda _1,\lambda _2)\)  follows by minimizing a performance metric computed at each grid point, depicted by shading at each point in Figure REF . Metrics such as Bayesian Information Criterion (BIC) or Akaike Information Criterion (AIC) may be computed using model degrees of freedom estimated by the number of unique covariate estimates [2]}.
